google Colab云GPU平台与Keras操作记录

谷歌云盘挂载：

from google.colab import drive

drive.mount('/content/drive/')

云盘挂载之后切换到代码目录：不能用！cd命令

import os
os.chdir('/content/drive/My Drive/CoLab/PCANet-Python')
os.getcwd()

导入第三方包：setup是包程序根目录的文件

!python3 setup.py install

或者在根目录执行：

pip3 install 

install Keras：

!pip install -q keras

下载dataset（.csv File）：

!wget https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/datasets/Titanic.csv -P "/content/drive/My Drive/app"

读取 .csv file 并展示 first 5 rows:

import pandas as pd
titanic = pd.read_csv(“/content/drive/My Drive/app/Titanic.csv”)
titanic.head(5)

克隆git-hub代码到colab：

Step 1: Find the Github Repo and Get “Git” Link（红色方框）

2. Git Clone：代码将下载到colab的My Driver下

!git clone https://github.com/wxs/keras-mnist-tutorial.git

然后就可以在colab的目录下执行代码了

Some Useful Tips

1. How to Install Libraries?

Keras

!pip install -q keras
import keras

PyTorch

from os import path
from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag
platform = '{}{}-{}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag())

accelerator = 'cu80' if path.exists('/opt/bin/nvidia-smi') else 'cpu'

!pip install -q http://download.pytorch.org/whl/{accelerator}/torch-0.3.0.post4-{platform}-linux_x86_64.whl torchvision
import torch

or try this:

!pip3 install torch torchvision

MxNet

!apt install libnvrtc8.0
!pip install mxnet-cu80
import mxnet as mx

OpenCV

!apt-get -qq install -y libsm6 libxext6 && pip install -q -U opencv-python
import cv2

XGBoost

!pip install -q xgboost==0.4a30
import xgboost

GraphViz

!apt-get -qq install -y graphviz && pip install -q pydot
import pydot

7zip Reader

!apt-get -qq install -y libarchive-dev && pip install -q -U libarchive
import libarchive

Other Libraries

!pip install or !apt-get install to install other libraries.

查看tensorboard：

tensorboard可以用来查看代码运行的中间变量、log及画出相应的曲线变化图。

其他操作tips参照：https://medium.com/deep-learning-turkey/google-colab-free-gpu-tutorial-e113627b9f5d